Abstract 185: Global mapping of pathway modules and phosphorylation networks in PDX and corresponding organoid (PDXO) models treated with targeted therapies
Authors: Martin Mehnert, Xiaoxi Xu, Tobias Treiber, Limei Shang, Leilei Chen, Jessie Wang, Marco Tognetti, Christopher Below, Roland Bruderer, Jakob Vowinckel, Binchen Mao, Wubin Qian, Sheng Guo, Ludovic Bourré, Yuehan Feng
Journal: Cancer Research (2023)

Abstract Introduction: Multi-omics-based strategies in precision medicine, including genomic, transcriptomic and proteomic data, have contributed to the molecular-level characterization of cancers and the identification of novel driver genes, as well as a better comprehension of resistance mechanisms. Patient-derived tumor models, including patient-derived xenograft (PDX) and in vitro 3D organoid counterparts (PDXO), are widely recognized as predictive preclinical cancer models closely recapitulating both tumor complexity and patient response and enabling the study of tumor identity for personalized medicine. Taking advantage of Crown Bioscience large PDX collection, with genomic and phenotypic annotation and pharmacological validation, a series of PDXO models have been established and characterized to be used as scalable and high throughput compatible drug screening platforms. Methods: Drug response in matched PDX and PDXO models were investigated on the functional and systems level through deep whole- and phospho-proteomic analysis. For this purpose, analysis and comparisons were made across dose and time series, the effect of several targeted therapies on protein expression and phosphorylation in both PDX and PDXO tumor models. More specifically, a KRAS inhibitor (AMG510), a BCR-ABL TKI (ponatinib) and an EGFR TKI (afatinib) were tested respectively in a lung NSCLC model carrying KRAS G12C mutation, a colorectal model with RET fusion and a lung NSCLC model with EGFR exon 19 deletion. Results: Based on previous data, a specific relationship between area under the curve (AUC) value of organoid drug dose response and in vivo tumor growth has been observed, irrespective of the drug treatment. To interrogate the pathways involved, both PDX and PDXO models were subjected to deep proteome and phospho-proteome profiling using state-of-the-art mass spectrometry-based workflows. An extensive dataset was generated where 16,797 proteins and 12,578 proteins were robustly quantified in PDX and PDXO models respectively. From the same samples, 35,403 phospho-sites were quantified across all PDX samples while 40,754 phospho-sites were quantified across all PDXO models. These data enabled the validation of known pathways (such as RAF/MEK/ERK, PI3K/AKT) and pinpoint new ones modulated through three small molecule inhibitors each targeting a defined genetic background. Conclusion: The predictivity of organoid cultures was demonstrated to model in vivo drug responses and also to serve as a powerful platform to investigate target identification, mechanism of action and resistance mechanism via functional proteome and phospho-proteome analysis. Citation Format: Martin Mehnert, Xiaoxi Xu, Tobias Treiber, Limei Shang, Leilei Chen, Jessie Wang, Marco Tognetti, Christopher Below, Roland Bruderer, Jakob Vowinckel, Binchen Mao, Wubin Qian, Sheng Guo, Ludovic Bourré, Yuehan Feng. Global mapping of pathway modules and phosphorylation networks in PDX and corresponding organoid (PDXO) models treated with targeted therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 185.